Research Methods Resources

step 3 in a research project



Research Methods Resources

Objectives and hypothesis

Quick links to some resources on this page

Make your study objectives clear, specific, complete ... !!!

Your research proposal (chapter 3.2 of The Green Book) (pdf 137 Kb)

What are you going to do to solve the researchable problem?

If you carried out an initial problem analysis and critically reviewed relevant literature on the topic, you have come up with a manageable and researchable problem and you have a thorough idea of the current state of knowledge on your research problem. You have done some assessment yourself on the relevance of the problem you want to address and how to cut it into manageable portions, but you relied much on the work of others you found in the literature.

This helps you to avoid some important pitfalls of any research project which are also important reasons why research papers are rejected for publication in peer reviewed journals (From box 3.1 on page 40 of Greenhalgh (2001)):

  • the study did not examine an important scientific issue

  • in other and more practical words: the study did not help in solving a relevant problem the society is facing

  • the study was not original - that is, someone else has already done the same or similar study



Greenhalgh, Trisha (2001) How to read a paper. The basics of evidence based medicine., BMJ Books, London. 222 p.

This book was originally published as a series of papers at Click here to go to the paper that contains the important reasons why research papers are rejected, or click here to go to a website that gives an overview of the whole series of papers.


But now your time has come. Setting the study objectives basically means that you tell what you are going to do to solve the researchable problem,  you explain the purpose of your research, you describe what you hope to achieve with your study, .... 

It is closely related with defining your hypothesis or hypotheses. A hypothesis is basically a testable hunch you have; what do you think is true based on what you know so far (i.e. problem analysis and literature review) and stated in a way that you can evaluate the strength of the evidence in favor of it.


Overall objectives, specific objectives, research questions, ....

There exist many schools of thought and traditions. What we present here might not necessarily correspond to the structure of a thesis or research report required by your institute. 

Some require to first define overall objectives (what you generally expect to learn from the study) in addition to specific objectives. Specifying overall objectives enables you to link your study with knowledge gaps in what has been done before (the top of the flow chart of the research process) and what should be done after this study (revise or move on to the next problem, see the bottom of the flow chart).

Others also require to state research questions in addition to your study objectives. Research questions lean already more towards the methods you will use: how are you going to do the experiment, sampling, survey, etc. Which treatments are needed to be able to address the objectives. We describe this in some of the next steps (research designs and formal analysis) as refining the study objectives for purposes of study design and formal analysis.

Using and adapting the framework we present will help you to come up with a solid, logical and useful researchable problem and one or more study objectives. Consult your supervisor on which structure is formally required and fit your logically derived study objectives into it.


 So far it has been a soup

"Science consists of both knowledge and the process by which this knowledge is created, research. Although research succeeds by building and testing better theories, the process involves constructs, concepts, and activities that are not themselves predictive. Non-predictive constructs serve science as logical devices, memory aids, inspirational prods, incentives to thought, political opinions, personal ideals, half-formed notions, odd beliefs, and unexpressed ideas. These elements are not 'bad' or unscientific. They form a prescientific soup from which each scientist draws inspiration and from which the disciplined human mind has constructed modern science.

Peters, Robert Henry (1991) A critique for ecology. Cambridge University Press, Cambridge, UK. 366 pp. ISBN 0 521 39588 7 - p. 21

So far we have described three distinct steps in your research project: delineating a problem into a researchable problem, literature review and setting study objectives and formulating hypotheses. In reality it is not possible to draw a clear line between those three steps, hence the up and down arrows in the flowchart on the right. 

The scientific method can be seen as a hypothetico-deductive method, many people see "the scientific method" and "the hypothetico-deductive method" as being synonyms. Much of the method is based upon the work of Sir Karl Popper.

Since we are now entering the realm of philosophy of science, it means we are at an abstract level and there exist lot of discussion between supporters and opponents of each philosophy. For a majority of research projects however, the hypothetico-deductive method is an appropriate framework for structuring your research process.

According to the philosophy behind the method, scientific research proceeds by formulating a hypothesis that is intended to explain an observation. From this hypothesis some predictions of further phenomena are deduced and tested. Observations that run contrary to those predicted are taken as a conclusive falsification of the hypothesis, observations which are in agreement with those predicted are taken as corroborating the hypothesis. A simplified flowchart is given below.


Although the method is called "hypothetico-deductive", you're likely to use a combination of different ways of reasoning, especially induction (inferring a general law or principle from the observation of particular instances) and deduction (inferring from generals to particulars).

In reality there is of course no clear distinction between a phase of inductive and deductive reasoning, just as there is no clear distinction between initial problem analysis, reviewing literature and formulating study objectives and hypotheses, as mentioned above.

You could however draw a clear line between what you have been doing until now and what you will do during the rest of your research project. The first phase until now has been quite anarchistic; a prescientific soup as Peters calls it. The formal name is the synthetic or private phase. While you think about a perceived problem, your thoughts get shape while being influenced by very many things: existing theory, your knowledge of this theory, your experience, your values and beliefs, your interests, influence from other people such as feedback from your supervisor, personal observations on the perceived problem for instance during field trips or previous work, ... It is a private  struggle during which you constantly switch between synthesising a working hypothesis, critical self-reflection and creativity.

The second phase, the analytic or public phase is much more structured and formal. It starts when your working hypotheses have stabilised into formal hypotheses. You are now ready to set up a study to test your hypothesis against data and publish the results of a critical analysis and interpretation so that other researchers can further evaluate it.


From logic to prediction: the importance of setting objectives.

Setting objectives is important for any decision maker. It is the starting point of the formal planning process for managers of enterprises and organisations (setting objectives, generating strategies, evaluating strategies, monitoring results and obtaining commitment). The same happens in everyday life at different levels. You strive towards certain big goals in your career, family life, ... but on a daily basis you constantly set yourself small objectives of a more practical nature such as "I want to finish this difficult job before the end of the week so that I can go on a trip this weekend."

If you don't have any goal to live or work to, you're likely to drift around in a confused state. Setting objectives provides structure, purposiveness, focus, meaning and enables you to measure progress in the right direction or the lack of it.

The same is true for your research. But here there is an extra dimension. Setting objectives, and especially spending enough time to develop well-developed clear and logical objectives, leads to  formal hypotheses which form the basis of the analytic phase of your research project. The framework of the analytic phase gives you a widely accepted formal structure to investigate how strong the evidence is in favor of your hypothesis and if the predictions made hold.

It will also help you to avoid another reason why research papers are rejected for publication in peer reviewed journals (From box 3.1 on page 40 of Greenhalgh (2001)):

  • the study did not actually test the authors’ hypothesis

All this basically means that doing a study without first setting objectives does not adhere to scientific quality standards.

"The objective is to compare treatments."

"Science has been called 'the art of the soluble' (Medawar 1967) because science succeeds by answering questions, not simply by posing them.

Peters, Robert Henry (1991) A critique for ecology. Cambridge University Press, Cambridge, UK. 366 pp. ISBN 0 521 39588 7 - p. 13

Medawar, P. (1967) The art of the soluble. Methuen, London, UK.

Just as when setting objectives in your personal life or when managing an organisation, also the objectives of your research should be:

  • clear and  unambiguous

  • complete

  • relevant to the researchable problem

  • capable of being met by some type of study (experiment, survey, a series of experiments, ....)

This cannot be stressed enough. Objectives drive the rest of the study: your hypothesis, the kind of study that needs to be done (experiment, survey, ....), the treatments that have to be compared, the population to be sampled, the data to be collected, the formal statistical analysis needed, ....

Making a vague statement such as "The objective is to compare treatments" is the same as setting no objectives at all. Information about "what?", "who?", "when?", "where?", "how many?", "how much?", .... should be incorporated in the study objectives.

Following objective is a real life example from a first draft of a research proposal:

Objective: To evaluate 4 improved mango varieties.

In the final research proposal, this had been improved to following clear statement from which the next steps to be taken flow automatically:
Objective: To determine whether the survival and growth rates, during the first two years, of improved mango varieties (Kent, Van Dyke, Tommy Atkins and Sensation) can be brought up to the level of the local variety by using a higher level of management (manure and water), when these trees are grown in crop fields of the coffee zone of Embu , Kenya.


Above we described a hypothesis as a hunch the researcher or research team have. You might define it in a more formal way, but basically a hypothesis is nothing more or less than a hunch to solve your research problem.

We are still in the domain of logic and communication although the word hypothesis has a statistical connotation because of the widespread practice of hypothesis testing. 


It is not important whether your hypothesis might be proved right or wrong by your study. Your research will be as valuable if it turns out to disprove your hypothesis. Communication of this result will help others to move on. Researchers tend to prefer a hypothesis that turns out correct, partly because of the human preference for winning instead of loosing, but also partly because of the philosophy behind the scientific method. Researchers tend to stick to previous results that have not been falsified. 

It is however of much greater importance to ensure that your hypothesis is manageable and being able to be tested by any kind of study.

A good hypothesis adds to existing theory by proposing rules, laws, processes and allows predictions to new situations.

You can often turn a vague statement into a good hypothesis by adding predictions on the how or why. So use sentences that include variations on "because of".

Example of vague statement: "Adoptability of improved fallow varies by gender."

Example of testable hypothesis that adds to current knowledge: "Women find improved fallow less adoptable than men because of labour shortages, low priority for maize production and lack of information."


A null-hypothesis is basically the opposite of a specific research question. 

The reason for this lies in philosophy behind the scientific method. To prove that something is true requires an inductive argument. Based on a series of observations, you induct a general statement that the phenomenon is true. There is however a problem with this kind of reasoning because it requires every possible observation to be available, or it requires the assumption that what happens in all possible circumstances not actually observed can be inferred from the cases actually available in the experiment. There is always a possibility that not enough evidence has been obtained and the contrary observation has not yet shown up. 

The solution is to use a "falsificationist procedure"; to prove that the opposite is not true. Once an observation has been made that disproves something, this something remains disproved for ever.

Defining a null-hypothesis might have some merit if the study you've set up requires the statistical tool of hypothesis testing. Generally it is much more informative to define a clear and detailed hypothesis and to evaluate the strength of evidence around it instead of simply proving or disproving the hypothesis.

Further resources

Muir-Leresche, Kay. 2004. Your research proposal. The Green Book. Chapter 3.2.


(137 Kb)
A PowerPoint Presentation by Wim Buysse and Ric Coe used during a training workshop for RUFORUM
Objectives and hypothesis.ppt (4,151 Kb)


 See the teaching tips given under Problem Analysis.


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